Yan Qiang

1.0k citations
83 papers · 695 · h-index 15

Impact in

Papers in

Yan Qiang

73 papers receiving 685 citations

Peers

Yan Qiang
Comparison fields: 5 of 120
  • Radiology, Nuclear Medicine and Imaging 244
  • Health Informatics 8
  • Cancer Research 72
  • Computer Vision and Pattern Recognition 116
  • Artificial Intelligence 136
Replace Juanjuan Zhao with:
Juanjuan Zhao China
Mehrdad J. Gangeh Canada
Yanlin Tan China
Ermanno Cordelli Italy
Mingon Kang United States
Antonio Foncubierta–Rodríguez Switzerland
Erdal Taşçı Türkiye
Pingjun Chen United States
Quang Hien Kha Taiwan
Yan Qiang relative to Juanjuan Zhao China Juanjuan Zhao's profile →
Citations per field
00.5×2×4×6×8×9×
Juanjuan Zhao · 1×
Citations per year

Countries citing papers authored by Yan Qiang

Since Specialization
Citations

This map shows the geographic impact of Yan Qiang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yan Qiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Qiang more than expected).

Fields of papers citing papers by Yan Qiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yan Qiang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yan Qiang. The network helps show where Yan Qiang may publish in the future.

Co-authors

The 25 scholars most cited alongside Yan Qiang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yan Qiang Line = papers co-authored together Yan Qiang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201352
2 202137
3 202237
4 201931
5 202025
6 201622
7
Augmented miR-10b expression associated with depressed expression of its target gene KLF4 involved in gastric carcinoma.
201521
8 201920
9 202218
10 201818
11 202317
12 202216
13 202315
14 202115
15 202015
16 201814
17
福建晋江中-基性岩墙群的锆石SHRIMP U-Pb定年和岩石地球化学
200613
18 202413
19 201311
20 202311

About Yan Qiang

Yan Qiang is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Cancer Research, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 83 papers that have together received 695 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (13 papers), Medical Imaging Techniques and Applications (8 papers), AI in cancer detection (8 papers), Advanced X-ray and CT Imaging (7 papers), Lung Cancer Diagnosis and Treatment (6 papers), Complex Network Analysis Techniques (6 papers), MicroRNA in disease regulation (5 papers) and Dementia and Cognitive Impairment Research (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (244 citations), Health Informatics (8 citations), Cancer Research (72 citations), Computer Vision and Pattern Recognition (116 citations) and Artificial Intelligence (136 citations). Yan Qiang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Juanjuan Zhao, Jing Zhang, Wei Wei, Wenbin Yuan, Long Wang, Kai Song, Xiaotang Yang, Wei Wu, Zijuan Zhao and Shi-Yu Zhou. Their work appears in journals such as Computers in Biology and Medicine, International Journal of Human-Computer Interaction, Biomedical Signal Processing and Control, International Journal of Computer Assisted Radiology and Surgery and Medical Physics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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